Customer service dynamic allocation methods, media and equipment applied to customer service systems

Abstract

This application provides a method, medium, and device for dynamic allocation of customer service in a customer service system. The method includes: obtaining task information of consultation tasks to be allocated; obtaining customer service information of customer service personnel; determining a consultation task allocation strategy based on the task information of the consultation tasks to be allocated and the customer service information of the customer service personnel; and allocating consultation tasks to customer service personnel based on the consultation task allocation strategy. Consultation tasks with the same order number are allocated to the same customer service personnel. This application considers that the same consultation task submitted by a customer and merchant with the same order number is allocated to the same online customer service representative for processing, providing the highest priority. This effectively alleviates problems such as information fragmentation, redundant communication, and low efficiency. Furthermore, it can assign appropriate processing priorities based on the different statuses of the orders associated with the consultation task, which is more in line with actual conditions and reduces the trust risk between customers and merchants and the platform.

Description

Technical Field

[0001] This application relates to the field of order after-sales service, and more specifically, to a method, medium, and device for dynamic allocation of customer service in a customer service system. Background Technology

[0002] With the rapid development of e-commerce, online service platforms, and the digital economy, online customer service systems have become a crucial bridge connecting service platforms and users. The queuing efficiency of a customer service system directly impacts user experience, service quality, and platform operational efficiency. Currently, the mainstream customer service queuing technologies in the industry can be categorized as follows: (1) The most basic First-In-First-Out (FIFO) algorithm is adopted, in which all customers form a queue according to the time of arrival of their requests, and customer service representatives provide services in the order of the queue. This method is simple to implement, but it completely ignores the differences between customers and the urgency of services, and cannot meet the needs of modern service platforms for refined operations. It also cannot dynamically adjust priorities according to customer type, service status, etc., resulting in high-value users or urgent services not receiving timely responses, affecting user experience and service efficiency.

[0003] (2) The concept of priority is introduced on the basis of FIFO. Fixed priority tags are assigned to customers based on their static attributes (such as VIP level, customer type, historical consumption amount, etc.), and high-priority customers can receive services first. This method solves the problem of priority service for important users to a certain extent, but the priority is static and cannot reflect the dynamic changes in the service process. Some advanced systems have also begun to introduce limited dynamic scheduling capabilities, such as matching based on customer service skills and routing based on service type, but these customer service systems still do not consider the urgency of the consultation tasks of both parties in the order. For example, a user who is currently receiving a service (such as a massage service) may need a more urgent response than a newly arrived VIP user. Or, for both parties in the order (customer and merchant) who are consulting (such as a complaint), the two parties may have had disputes and each has their own version of events, and the response needs to be more timely, but the static priority system cannot recognize such dynamic needs.

[0004] In addition, for order service scenarios involving multiple parties (such as when users and merchants consult about the same order), the existing system lacks an effective reception binding mechanism, which may result in different parties involved in the same order being assigned to different customer service representatives, causing problems such as information fragmentation, duplicate communication, and low efficiency. Summary of the Invention

[0005] The purpose of this application is to provide a method, medium, and device for dynamic allocation of customer service in a customer service system. This method considers the same inquiry task submitted by a customer and merchant with the same order number and assigns it to the same online customer service representative for processing. (If the original customer service representative is offline, a snapshot of the historical inquiry task needs to be provided so that the new representative can quickly understand the service status of the historical inquiry task and better serve the new inquiry task.) It has the highest priority processing level, effectively alleviating problems such as information fragmentation, redundant communication, and low efficiency. Furthermore, it can assign appropriate processing priority levels based on the different statuses of the orders associated with the inquiry task, which is more in line with actual conditions and reduces the trust risk between customers and merchants and the platform.

[0006] To achieve the above objectives, the embodiments of this application are implemented in the following manner: In a first aspect, embodiments of this application provide a method for dynamically allocating customer service in a customer service system, comprising: obtaining task information of consultation tasks to be allocated, wherein each task information includes the task initiation time, order number, order status, order customer, order merchant, task type, and task object associated with the consultation task, wherein the task object is the order customer or the order merchant; obtaining customer service information of customer service personnel, wherein the customer service information includes customer service ID, customer service status, customer service type, and customer service capabilities; determining a consultation task allocation strategy based on the task information of the consultation tasks to be allocated and the customer service information of the customer service personnel, and allocating consultation tasks to customer service personnel based on the consultation task allocation strategy, wherein consultation tasks with the same order number are allocated to the same customer service personnel.

[0007] In conjunction with the first aspect, in the first possible implementation of the first aspect, a consultation task allocation strategy is determined based on the task information of the consultation task to be allocated and the customer service information of the customer service personnel. This includes: for each consultation task to be allocated: determining whether there is a customer service ID associated with the order number of the consultation task; if so, determining the allocation target of the current consultation task based on the customer service information of the customer service personnel corresponding to the customer service ID, wherein the customer service status includes offline and online, offline means that the customer service personnel cannot currently accept consultation tasks, and online means that the customer service personnel can currently accept consultation tasks, and the allocation target of the consultation task is the customer service personnel whose customer service status is online; if not, determining the priority score of the consultation task based on the task initiation time, order status, order customer, order merchant, and task object, and determining the allocation target of the consultation task based on the priority score of the consultation task and the customer service information of the customer service personnel.

[0008] In conjunction with the first possible implementation of the first aspect, in the second possible implementation of the first aspect, the allocation target of the current consultation task is determined based on the customer service information of the customer service personnel corresponding to the customer service ID. This includes: determining whether the customer service status of the customer service personnel corresponding to the customer service ID is offline; if not, determining the customer service personnel corresponding to the customer service ID as the allocation target of the current consultation task; if so, determining the historical consultation tasks associated with the current consultation task, and based on the historical consultation tasks and the current consultation task, determining the allocation target of the current consultation task from the online customer service personnel. Here, the historical consultation task refers to the consultation task with the same order number as the current consultation task, and the consultation object of the historical consultation task is the same as or different from the consultation object of the current consultation task.

[0009] In conjunction with the first possible implementation of the first aspect, in the third possible implementation of the first aspect, the priority score of the consultation task is determined based on the task initiation time, order status, order customer, order merchant, and task object. This includes: if the order status of the consultation task is "service," the current consultation task is classified as the first category, where the order status includes "order placed," "payment," "service," and "completion." If the order status of the consultation task is "payment" or "completion," and the task object is the order customer, the current consultation task is classified as the second category. If the order status of the consultation task is "order placed," and the task object is the order customer, the current consultation task is classified as the third category. If the order status of the consultation task is "order placed," "payment," or "completion," and the task object is the order merchant, the current consultation task is classified as the second or third category based on the merchant information of the order merchant. The priority score of the consultation task is calculated based on the category and initiation time of the consultation task.

[0010] In conjunction with the third possible implementation of the first aspect, in the fourth possible implementation of the first aspect, the priority score of the consultation task is calculated based on the category and initiation time of the consultation task, including: calculating the priority score of the consultation task in the following manner: , in, For consulting tasks Priority score, For consulting tasks Category scores, For consulting tasks Task initiation time Used as the base time.

[0011] In conjunction with the first possible implementation of the first aspect, in the fifth possible implementation of the first aspect, the allocation target of the consultation task is determined based on the priority score of the consultation task and the customer service information of the customer service personnel. This includes: sorting the unassigned consultation tasks based on their priority scores, wherein if there are consultation tasks with the same priority score, the consultation tasks with the same priority score are sorted based on the task initiation time; for each sorted consultation task: matching the task information of the current consultation task and the object information of the consultation object with the customer service information of the customer service personnel to determine the matching customer service personnel as the allocation target of the current consultation task.

[0012] In conjunction with the first aspect, in the sixth possible implementation of the first aspect, customer service personnel are assigned consultation tasks based on the consultation task allocation strategy, including: for each consultation task with a determined allocation target: if the current consultation task has associated historical consultation tasks, and the allocation target corresponding to the current consultation task is inconsistent with the allocation target of the historical consultation tasks, the snapshot information of the historical consultation tasks is obtained, and the current consultation task is assigned together with the current consultation task to the allocation target corresponding to the current consultation task, and the allocation target corresponding to the historical consultation tasks is updated; if the current consultation task does not have associated historical consultation tasks, the current consultation task is assigned to the corresponding allocation target.

[0013] In conjunction with the sixth possible implementation of the first aspect, the seventh possible implementation of the first aspect involves obtaining snapshot information of historical consultation tasks, including: obtaining basic order information corresponding to the historical consultation task, which includes order number, product name, order amount, order time, order status, order customer, and order merchant; obtaining customer information corresponding to the order customer and merchant information corresponding to the order merchant; obtaining service records corresponding to the historical consultation task, which includes several items such as consultation type, problem description summary, user expected solution, merchant response summary, key evidence, key customer service commitments, customer emotion change nodes, and service progress; and generating snapshot information corresponding to the historical consultation task based on the basic order information, customer information, merchant information, and service records.

[0014] Secondly, embodiments of this application provide a storage medium installed in an electronic device, including a stored program, wherein, when the program is running, it controls the electronic device containing the storage medium to execute the dynamic allocation method for customer service in a customer service system as described in the first aspect or any possible implementation thereof.

[0015] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor. The memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, they implement the steps of the dynamic allocation method for customer service in a customer service system as described in the first aspect or any of the possible implementations of the first aspect.

[0016] Beneficial effects: This solution, after obtaining the task information for the consultation tasks to be assigned, obtains the customer service information of the customer service personnel. Then, based on the task information and the customer service personnel's information, it determines the consultation task allocation strategy and assigns consultation tasks to customer service personnel according to this strategy. Consultation tasks with the same order number are assigned to the same customer service personnel. (Here, if the original customer service representative is offline, a snapshot of historical consultation tasks needs to be provided to the new representative so that they can quickly understand the service status of past consultation tasks and better serve new consultation tasks.) Traditional customer service systems often lack an effective binding mechanism when handling inquiries involving users and merchants regarding the same order, resulting in both parties being assigned to different customer service representatives, causing information fragmentation, duplicate communication, and efficiency losses. This solution solves this problem through its core design of assigning consultation tasks with the same order number to the same customer service representative (if the original customer service representative is offline, a snapshot of historical consultation tasks needs to be provided to the new representative, as such inquiries involve multiple or two-way consultations, which are situations that could easily cause customers or merchants to lose trust in the platform and need to be handled as soon as possible; therefore, customer service personnel are assigned to these cases with the highest priority). Specifically, when a new consultation task enters the system, the system first checks if the order already has an associated customer service ID. If it does, and the customer service representative is online, the task is directly assigned to that representative. If the representative is offline, a matching assignment target is selected from the online customer service pool. This binding mechanism not only ensures that consultation tasks for the same order are handled by the same customer service representative throughout the entire process, avoiding service gaps caused by representative switching, but also, when the original representative is offline, integrates historical consultation task snapshot information (including basic order information, customer / merchant information, service records, and other key content), enabling new customer service representatives to quickly obtain key information and key service nodes when taking over a new task, thereby improving problem-solving efficiency and user satisfaction. Compared to static priority systems that only focus on customer attribute tags, this solution's dynamic binding mechanism achieves a strong association between orders and customer service representatives, effectively solving the pain point of information fragmentation in multi-party consultation scenarios.

[0017] Traditional static priority systems allocate priorities based on static customer attributes (such as customer level, VIP status, etc.), failing to respond to dynamic changes during the service process (e.g., a user receiving a massage service may require a more urgent response). This solution incorporates a refined dynamic priority design in its allocation strategy, using a composite priority calculation scheme of "category score + time factor" to quantify the urgency of consultation tasks. Specifically, the system categorizes tasks into three levels based on order status (order placed, paid, serviced, completed) and task recipient (customer / merchant). Tasks in the service status are assigned the highest category score, ensuring that users currently receiving service receive the highest response priority when task initiation times are not significantly different. Simultaneously, a decay factor based on task initiation time is introduced, giving higher priority to earlier initiated tasks and minimizing user experience degradation due to excessive waiting times. In terms of allocation strategy, the system first sorts unassigned tasks based on priority scores, then performs a secondary matching based on customer service capabilities (e.g., expertise in handling certain order types of consultation tasks) and status (online / offline), ensuring that consultation tasks are handled by suitable customer service representatives. This dynamic adjustment mechanism not only solves the problem of static priority systems failing to identify urgent needs in the service process, but also ensures service continuity and the integrity of problem resolution through a combined allocation model of historical task snapshots and new tasks, thereby improving user experience and service efficiency. Furthermore, snapshot information can also address the pain point of information gaps when switching customer service representatives. For example, if a customer or merchant is dissatisfied with a customer service representative and requests a change, snapshot information can effectively resolve this pain point. The new customer service representative can quickly understand the previous communication, recognize the emotional shifts of the customer / merchant, and thus better provide service and resolve problems, reducing the risk of trust issues for customers and merchants with the platform.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an architecture diagram of the customer service system.

[0021] Figure 2 A flowchart illustrating the dynamic allocation method for customer service in a customer service system.

[0022] Figure 3 This is a schematic diagram of the customer service system interface. Detailed Implementation

[0023] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0024] Please see Figure 1 , Figure 1 This is an architecture diagram of the customer service system.

[0025] In this embodiment, the customer service system mainly includes a data acquisition layer, a calculation and scheduling layer, a service execution layer, and an application layer.

[0026] The data acquisition layer is primarily used to retrieve relevant data from the database, providing data acquisition services. The collected data includes order information, merchant information, and user information. For example, it retrieves static attribute data such as basic user information, historical order records, customer levels, and service preferences from the user center system, and synchronizes this data with the user database in real time via API interfaces to ensure the accuracy of user identity information and value assessment. It also interfaces with the merchant management system to obtain key information such as merchant authentication status, service qualifications, and historical order records, enabling it to identify whether a merchant is a member merchant—a crucial basis for priority calculation. Furthermore, it can monitor order system status changes in real time, track key nodes in the order lifecycle, continuously poll the order status database, and capture the entire process of order status changes from order placement to service completion (e.g., order placement-payment-service-completion status).

[0027] The service execution layer mainly includes a queue status manager, a reception allocator, and a role filter. The queue status manager is used to sort and manage the queue according to the priority of the consultation task; the role filter is mainly used to filter different types of customer service, such as pre-sales customer service, after-sales customer service, complaint customer service, quality inspection customer service, spot check customer service, and other customer service, etc. The solution provided in this embodiment mainly uses pre-sales customer service, after-sales customer service, and complaint customer service; the reception allocator is mainly used to assign customer service to consultation tasks.

[0028] The computational scheduling layer is mainly used for service level assessment, priority score calculation, sorting, traffic control, and client binding.

[0029] The application layer includes a customer service workbench and a client application, which is used by both merchants and customers.

[0030] The overall architecture of the customer service system forms the foundation for implementing dynamic customer service allocation methods. Please refer to [link / reference needed]. Figure 2 , Figure 2This is a flowchart of a dynamic customer service allocation method applied to a customer service system. In this embodiment, the dynamic customer service allocation method may include steps S10, S20, and S30.

[0031] When customers or merchants need to make inquiries, they can initiate an inquiry task through the order portal in the client application. It should be noted that this embodiment is for inquiry tasks primarily based on orders (such as pre-sales, after-sales, and complaint-related inquiries). Other types of inquiries (such as direct inquiries without orders) are not within the scope of this embodiment.

[0032] At this point, the customer service system can proceed to step S10.

[0033] Step S10: Obtain the task information of the consultation tasks to be assigned. Each task information includes the task initiation time, order number, order status, order customer, order merchant, task type, and task object associated with the consultation task. The task object is the order customer or the order merchant.

[0034] In this embodiment, the customer service system can obtain task information for consultation tasks to be assigned. Each task information includes the task initiation time (accurate to the second, including year, month, day, hour, minute, and second), order number (this order number is the order number after the user places the order, not the consultation task number), order status (including order status, payment status, service status, and completion status; order status indicates the customer has placed an order but not paid; payment status indicates the customer has placed an order and paid; service status indicates the merchant is providing service to the customer; completion status indicates the service has been completed), order customer (i.e., the customer of this order), order merchant (i.e., the merchant of this order), task type (i.e., the type of consultation task, such as complaint, pre-sales consultation, after-sales consultation, etc.), and task object (the task object is the order customer or the order merchant). Of course, each consultation task can also be assigned a corresponding task number, but in this embodiment, the task number is optional.

[0035] After obtaining the task information for the consultation tasks to be assigned, the customer service system can proceed to step S20.

[0036] Step S20: Obtain customer service information of customer service personnel, including customer service ID, customer service status, customer service type, and customer service capabilities.

[0037] In this embodiment, the customer service system can obtain customer service information of customer service personnel within the system. The customer service information includes customer service ID (each customer service representative has a unique customer service ID), customer service status (offline, online; in other embodiments, it can be further subdivided to reflect the real-time workload of the customer service representative, thereby determining whether the customer service representative can take on new consultation tasks), customer service type (such as pre-sales customer service, after-sales customer service, and complaint customer service), and customer service capabilities (such as being good at handling pre-sales consultations, handling complaints, and handling after-sales consultations).

[0038] Accordingly, the customer service system can proceed to step S30.

[0039] Step S30: Based on the task information of the consultation tasks to be assigned and the customer service information of the customer service personnel, determine the consultation task allocation strategy, and allocate consultation tasks to the customer service personnel based on the consultation task allocation strategy. Consultation tasks with the same order number are assigned to the same customer service personnel.

[0040] In this embodiment, for each consultation task to be assigned, the customer service system can determine whether there is a customer service ID associated with the order number of the consultation task. This determination mainly involves checking whether there has been a previous consultation for the order number corresponding to this consultation task. A previous consultation refers to a consultation initiated by a merchant or customer for this order, and a customer service representative was assigned to provide consultation services. Additionally, this embodiment uses the online status of the customer service representative as a criterion. Other embodiments may also consider whether the customer service representative is online and has not reached the task limit (for example, a customer service representative's capacity is to handle a maximum of 8 consultation tasks simultaneously, excluding voice call-based consultations).

[0041] If a customer service ID is associated with the order number of the consultation task, the customer service system can determine the target of the current consultation task based on the customer service information of the customer service personnel corresponding to the customer service ID. The customer service status includes offline and online. Offline means that the customer service personnel cannot accept consultation tasks at present, and online means that the customer service personnel can accept consultation tasks at present. The target of the consultation task is the customer service personnel whose customer service status is online.

[0042] For example, the customer service system can determine whether the customer service status of the customer service personnel corresponding to the customer service ID is offline. If the customer service status is not offline, the customer service system can determine that the customer service personnel corresponding to the customer service ID is the allocation target for the current consultation task. If the customer service status is offline, it is necessary to determine the historical consultation tasks associated with the current consultation task (historical consultation tasks refer to consultation tasks corresponding to the same order number as the current consultation task). The consultation object of the historical consultation task is the same as or different from the consultation object of the current consultation task. That is, it can be a consultation task initiated by the same consultation object for this order number before, or it can be a consultation task initiated by different consultation objects for this order number. Then, based on the historical consultation tasks and the current consultation task, the allocation target for the current consultation task is determined from the online customer service personnel. The way to determine the allocation target for the current consultation task from the online customer service personnel can be based on the task type of the consultation task (it can be distinguished from consultation or complaint based on the entry point of the merchant or customer to the consultation, and based on the order status to distinguish from pre-sales consultation or after-sales consultation), and the customer service personnel with matching customer service types can be selected from the online customer service personnel as the allocation target for the consultation task.

[0043] If there is no customer service ID associated with the order number of the consultation task, the customer service system can determine the priority score of the consultation task based on the task initiation time, order status, order customer, order merchant, and task object, and determine the allocation target of the consultation task based on the priority score of the consultation task and the customer service information of the customer service personnel.

[0044] For example, the customer service system can categorize consultation tasks based on order status. The order status of a consultation task includes order status, payment status, service status, and completion status.

[0045] If the order status of a consultation task is "service", the customer service system can determine that the current consultation task belongs to the first category.

[0046] If the order status of a consultation task is either paid or completed, and the task recipient is the order customer, then the current consultation task is classified as the second category.

[0047] If the order status of the consultation task is "order placed" and the task target is the order customer, then the current consultation task is determined to be in the third category.

[0048] If the order status of a consultation task is "order placed," "paid," or "completed," and the task recipient is the order merchant, then the current consultation task is determined to be either Category II or Category III based on the merchant's information. For example, if the merchant's information includes the merchant's membership status (or level, rating, or other methods for differentiating merchants, primarily used to distinguish merchant quality), then if the merchant is a member, the current consultation task is classified as Category II; if the merchant is not a member, the current consultation task is classified as Category III.

[0049] Afterwards, the customer service system can calculate the priority score of the consultation task based on the category and initiation time of the consultation task.

[0050] For example, a customer service system can calculate the priority score of a consultation task in the following way: , (1) in, For consulting tasks Priority score, For consulting tasks Category scores (for category scores) In this embodiment, the first category is assigned a value of 3, the second category is assigned a value of 2, and the third category is assigned a value of 1. For consulting tasks The task initiation time (format can be: year-month-day-hour:minute:second, for example 2025-06-16-11:25:42). The base time (the format can be: year-month-day-hour:minute:second, where the time is the set time, such as setting it to the start time of each day, such as 2025-06-16-09:00:00, or setting it to the start time of each day, such as 2025-06-16-00:00:00). and For weight parameters, , and The parameter values ​​need to be set in advance, for example, each of them should be 0.5, or they can be allocated according to 0.7:0.3. In this embodiment, we take each of them as 0.5 (this will ensure that categories with higher category scores are always processed first).

[0051] After the priority score of the consultation task is completed, the customer service system can sort the unassigned consultation tasks based on their priority scores. If there are consultation tasks with the same priority score, they are sorted based on the task initiation time.

[0052] For each sorted consultation task: the customer service system can match the task information and the object information of the consultation target with the customer service information of the customer service personnel to determine the matching customer service personnel as the assignment target for the current consultation task.

[0053] The matching here mainly involves matching task types with customer service types, and also checking whether the customer service representative can accept new consultation tasks. This differs from the previous solution for tasks with historical consultations. For consultation tasks with order numbers that have historical consultations, this embodiment will process them promptly, without using customer service capability (i.e., whether the customer service representative can take on new consultation tasks) as an absolute reference indicator (although it will try to assign them to customer service representatives with matching customer service types and fewer current consultation tasks), ensuring that consultation tasks with historical consultations are assigned promptly. For consultation tasks sorted by priority score (consultation tasks with order numbers that do not have historical consultations), customer service capability (i.e., whether the customer service representative can take on new consultation tasks) needs to be considered, and the customer service capability limit must not be exceeded (i.e., the maximum number of tasks that can be processed at the same time, for example, no more than 8). Of course, this embodiment mainly focuses on conversational consultations; for voice call consultations, a dedicated voice customer service representative is currently assigned to handle the transfer.

[0054] When a new consultation task comes in, after the previous processing, if it is a consultation task with an order number that has a history of consultation tasks, it will be directly assigned to a customer service representative; if the consultation task with an order number that has no history of consultation tasks, its priority score needs to be calculated and then it will be placed in the sorting queue.

[0055] Considering the possibility of long queue times for consultation tasks with low category scores, and to prevent these tasks from remaining unprocessed for extended periods (although this is rare, it theoretically exists because new consultation tasks are constantly being added; if low-category tasks are already in the queue and new high-category tasks keep jumping the queue, low-category tasks may remain in the queue indefinitely, making it impossible to determine their allocation), a real-time monitoring mechanism needs to be designed to promptly process queued tasks and improve their processing priority.

[0056] The real-time monitoring mechanism can be designed as follows: the customer service system obtains the list of queued consultation tasks in real time (the acquisition frequency can be once every 1 second), and determines whether there are any target consultation tasks in the consultation task list whose time difference between the task initiation time and the current time exceeds a set value (such as 30 minutes or 20 minutes). If so, the target consultation task is promoted to the front of the queue (if there are multiple target consultation tasks, they are sorted according to their priority scores and placed at the front of the queue). This can avoid the situation where a consultation task may not be processed for a long time.

[0057] For each consultation task with a defined allocation target, if the current consultation task has associated historical consultation tasks, and the allocation target for the current consultation task differs from that of the historical consultation tasks, the customer service system needs to obtain a snapshot of the historical consultation tasks, assign it along with the current consultation task to the allocation target corresponding to the current consultation task, and update the allocation target corresponding to the historical consultation tasks. If the current consultation task has no associated historical consultation tasks, the customer service system can assign the current consultation task to the corresponding allocation target. The customer service personnel's interface is as follows: Figure 3 As shown.

[0058] In this embodiment, the customer service system needs to obtain key information such as the basic order information, customer information, merchant information, and customer service records corresponding to the historical consultation tasks.

[0059] Basic order information includes order number, product name, order amount, order time, order status, order customer, and order merchant. Customer information includes static attributes such as customer ID, customer level, and customer preferences. Merchant information includes key information such as merchant ID, merchant authentication status, service qualifications, and historical order records. Customer service records include the consultation type, problem description summary, user (mainly customer) expected solution, merchant response summary, key evidence, key customer service commitments, customer emotional changes, and several items related to service progress (these items should be collected as much as possible, as the service status of historical consultations is usually unresolved or the solution is not yet complete). Service records can be manually recorded by customer service representatives after completing a consultation session (completing the session indicates the end of the consultation task, but does not necessarily mean the customer's or merchant's consultation needs have been resolved).

[0060] In addition, to improve the efficiency of customer service consultation processing, future optimizations plan to introduce a locally deployed AI model to generate communication points based on service records (along with snapshot information corresponding to historical consultation tasks, and sent to the customer service personnel corresponding to the current consultation task). This will provide assistance to customer service personnel, making it easier for them to communicate and verify with the consultation recipient in the current consultation task based on the communication points, thereby improving the efficiency of consultation services.

[0061] For example, if the order number associated with the current consultation task has a related historical consultation task, the relevant information of the historical consultation task (such as the historical service records, order information, customer information, merchant information, etc.) is input into the locally deployed AI model. The AI ​​model analyzes the data and generates structured auxiliary information, which may include several modules such as core issues, communication content, to-do items, and reminders.

[0062] Example Scenario 1: Three days ago, a customer complained about the merchant's poor service and rude behavior, and requested a refund. Customer service promised to reply within 24 hours, but did not call back. The customer called back again.

[0063] The core issue: A customer requested a refund due to the merchant's poor service attitude, but customer service failed to fulfill its promise to call back, and the problem remains unresolved.

[0064] Communication received: Customer service complained about the merchant's poor behavior and requested a refund. The previous customer service representative recorded the complaint and promised a callback within 24 hours, but no callback was made. The customer did not contact the customer again until this latest call.

[0065] To be done: Fulfill the unfulfilled promise to call back, apologize to the customer and immediately check the progress of the complaint handling, and clearly inform them of the refund processing result.

[0066] Reminder: It is advisable to apologize at the beginning to avoid customer dissatisfaction.

[0067] Example Scenario 2: A merchant inquires about discrepancies in reconciliation, but the system cannot find the settlement record.

[0068] Key issue: Merchants reported that the bill amount did not match their expectations, and the system backend could not find the settlement record for the corresponding period. It is necessary to verify the transaction flow and settlement status.

[0069] Content communicated so far: The merchant provided a reconciliation period from February 1, 2026 to February 28, 2026. The system backend shows that there are 3 refunds that are not reflected in the merchant's bill within this period. The previous customer service representative informed us that the matter would be forwarded to the finance department for verification.

[0070] To be done: It is recommended that customer service promise the merchant that "the transaction record verification will be completed within 1-2 business days, and the details of the discrepancies, the reasons, and the results will be provided via email or system message".

[0071] Reminder: It is recommended to proactively explain the verification steps and the expected feedback time to reduce merchants' anxiety.

[0072] This embodiment provides a storage medium installed in an electronic device, which includes a stored program. When the program runs, it controls the electronic device containing the storage medium to execute the dynamic customer service allocation method of this embodiment applied to a customer service system.

[0073] Furthermore, this application embodiment also provides an electronic device, including a memory and a processor. The memory is used to store information of program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, they implement the steps of the dynamic allocation method for customer service in the customer service system of this embodiment.

[0074] In summary, this application provides a method, medium, and device for dynamic allocation of customer service in a customer service system. After obtaining the task information of the consultation task to be allocated, the system obtains the customer service information of the customer service personnel. Then, based on the task information of the consultation task to be allocated and the customer service information of the customer service personnel, a consultation task allocation strategy is determined, and consultation tasks are allocated to the customer service personnel based on the strategy. Consultation tasks with the same order number are assigned to the same customer service personnel. (Furthermore, if the original customer service representative is offline, a snapshot of historical consultation tasks needs to be provided to the new customer service representative so that the new representative can quickly understand the service status of historical consultation tasks and better provide services for new consultation tasks.) Traditional customer service systems often lack an effective binding mechanism when handling inquiries involving users and merchants regarding the same order, resulting in both parties being assigned to different customer service representatives, causing information fragmentation, redundant communication, and efficiency losses. This solution addresses this issue by assigning consultation tasks with the same order number to the same customer service representative. (If the original representative is offline, a snapshot of historical consultation tasks must be provided to the new representative, as such consultations involve multiple or bilateral inquiries, which could potentially erode customer or merchant trust in the platform and require prompt handling; therefore, they are assigned to customer service representatives with the highest priority.) Specifically, when a new consultation task enters the system, it first checks if the order already has an associated customer service ID. If so, and the representative is online, the task is directly assigned to that representative. If the representative is offline, a matching assignment is selected from online representatives. This binding mechanism not only ensures that consultation tasks for the same order are handled by the same representative throughout, avoiding service gaps caused by representative switching, but also, when the original representative is offline, integrates historical consultation task snapshot information (including basic order information, customer / merchant information, service records, and other key content), allowing the new representative to quickly access key information and service milestones when taking on a new task, thereby improving problem-solving efficiency and user satisfaction. Compared to static priority systems that only focus on customer attribute tags, this solution's dynamic binding mechanism achieves a strong association between orders and customer service, effectively solving the pain point of information fragmentation in multi-party consultation scenarios.

[0075] Traditional static priority systems allocate priorities based on static customer attributes (such as customer level, VIP status, etc.), failing to respond to dynamic changes during the service process (e.g., a user receiving a massage service may require a more urgent response). This solution incorporates a refined dynamic priority design in its allocation strategy, using a composite priority calculation scheme of "category score + time factor" to quantify the urgency of consultation tasks. Specifically, the system categorizes tasks into three levels based on order status (order placed, paid, serviced, completed) and task recipient (customer / merchant). Tasks in the service status are assigned the highest category score, ensuring that users currently receiving service receive the highest response priority when task initiation times are not significantly different. Simultaneously, a decay factor based on task initiation time is introduced, giving higher priority to earlier initiated tasks and minimizing user experience degradation due to excessive waiting times. In terms of allocation strategy, the system first sorts unassigned tasks based on priority scores, then performs a secondary matching based on customer service capabilities (e.g., expertise in handling certain order types of consultation tasks) and status (online / offline), ensuring that consultation tasks are handled by suitable customer service representatives. This dynamic adjustment mechanism not only solves the problem of static priority systems failing to identify urgent needs in the service process, but also ensures service continuity and the integrity of problem resolution through a combined allocation model of historical task snapshots and new tasks, thereby improving user experience and service efficiency. Furthermore, snapshot information can also address the pain point of information gaps when switching customer service representatives. For example, if a customer or merchant is dissatisfied with a customer service representative and requests a change, snapshot information can effectively resolve this pain point. The new customer service representative can quickly understand the previous communication, recognize the emotional shifts of the customer / merchant, and thus better provide service and resolve problems, reducing the risk of trust issues for customers and merchants with the platform.

[0076] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for dynamically allocating customer service requests in a customer service system, characterized in that, include: Get the task information of the consultation tasks to be assigned. Each task information includes the task initiation time, order number, order status, order customer, order merchant, task type, and task object associated with the consultation task. The task object is the order customer or the order merchant. Obtain customer service information from customer service personnel, including customer service ID, customer service status, customer service type, and customer service capabilities. Based on the task information of the consultation tasks to be assigned and the customer service information of the customer service personnel, a consultation task allocation strategy is determined, and consultation tasks are assigned to customer service personnel based on the consultation task allocation strategy. Consultation tasks with the same order number are assigned to the same customer service personnel.

2. The dynamic allocation method for customer service in a customer service system according to claim 1, characterized in that, Based on the task information of the consultation tasks to be assigned and the customer service information of the customer service personnel, a consultation task assignment strategy is determined, including: For each consulting task to be assigned: Determine if a customer service ID exists that is associated with the order number of the consultation task; If it exists, determine the target of the current consultation task based on the customer service information of the customer service personnel corresponding to the customer service ID. The customer service status includes offline and online. Offline means that the customer service personnel cannot accept consultation tasks at present, and online means that the customer service personnel can accept consultation tasks at present. The target of the consultation task is the customer service personnel whose customer service status is online. If not, determine the priority score of the consultation task based on the task initiation time, order status, order customer, order merchant, and task target. Then, determine the allocation target of the consultation task based on the priority score of the consultation task and the customer service information of the customer service personnel.

3. The dynamic allocation method for customer service in a customer service system according to claim 2, characterized in that, Based on the customer service information of the customer service personnel corresponding to the customer service ID, determine the allocation target of the current consultation task, including: Determine if the customer service status of the customer service person corresponding to the customer service ID is offline; If not, determine the customer service personnel corresponding to the customer service ID as the target for the current consultation task; If so, identify the historical consultation tasks associated with the current consultation task, and based on the historical consultation tasks and the current consultation task, determine the allocation target of the current consultation task from the online customer service personnel. Here, the historical consultation task refers to the consultation task with the same order number as the current consultation task, and the consultation object of the historical consultation task may be the same as or different from the consultation object of the current consultation task.

4. The dynamic allocation method for customer service in a customer service system according to claim 2, characterized in that, Based on the task initiation time, order status, order customer, order merchant, and task recipient, a priority score is determined for each consultation task, including: If the order status of a consultation task is "service status", then the current consultation task is classified as the first category. The order status of a consultation task includes "order placed", "payment status", "service status", and "completion status". If the order status of the consultation task is paid or completed, and the task recipient is the order customer, then the current consultation task is classified as the second category. If the order status of the consultation task is "order placed" and the task recipient is the order customer, then the current consultation task is classified as the third category. If the order status of the consultation task is "order placed", "payment", or "completed", and the task recipient is the order merchant, the current consultation task is determined to be either the second or third category based on the merchant information of the order merchant. The priority score of a consultation task is calculated based on its category and initiation time.

5. The dynamic allocation method for customer service in a customer service system according to claim 4, characterized in that, Based on the category and initiation time of the consulting task, a priority score is calculated for the consulting task, including: The priority score for consulting tasks is calculated using the following method: ， in, For consulting tasks Priority score, For consulting tasks Category scores, For consulting tasks Task initiation time Used as the base time.

6. The dynamic allocation method for customer service in a customer service system according to claim 2, characterized in that, Based on the priority scores of consultation tasks and the customer service information of customer service personnel, the allocation goals for consultation tasks are determined, including: The consultation tasks are sorted based on their priority scores. If there are consultation tasks with the same priority score, they are sorted based on the task initiation time. For each sorted consultation task: based on the task information of the current consultation task and the object information of the consultation object, match them with the customer service information of the customer service personnel to determine the matching customer service personnel as the assignment target of the current consultation task.

7. The dynamic allocation method for customer service in a customer service system according to claim 1, characterized in that, Consultation tasks are assigned to customer service personnel based on a consultation task allocation strategy, including: For each consulting task with a defined assigned objective: If the current consultation task has associated historical consultation tasks, and the allocation target corresponding to the current consultation task is inconsistent with the allocation target of the historical consultation task, obtain the snapshot information of the historical consultation task, allocate it together with the current consultation task to the allocation target corresponding to the current consultation task, and update the allocation target corresponding to the historical consultation task. If the current consulting task has no associated historical consulting tasks, the current consulting task will be assigned to the corresponding allocation target.

8. The dynamic allocation method for customer service in a customer service system according to claim 7, characterized in that, Obtain snapshot information of historical consultation tasks, including: Obtain basic order information corresponding to historical consultation tasks. Basic order information includes order number, product name, order amount, order time, order status, order customer, and order merchant. Obtain customer information corresponding to the order customer and merchant information corresponding to the order merchant; Obtain service records corresponding to historical consultation tasks. Service records include several items such as consultation type, problem description summary, user expected solution, merchant response summary, key evidence status, key customer service commitments, customer emotion change nodes, and service progress. Based on the basic order information, customer information, merchant information, and service records corresponding to historical consultation tasks, snapshot information corresponding to historical consultation tasks is generated.

9. A storage medium, characterized in that, The storage medium is installed in an electronic device and includes a stored program, wherein when the program is executed, it controls the electronic device containing the storage medium to execute the dynamic customer service allocation method for a customer service system as described in any one of claims 1 to 8.

10. An electronic device comprising a memory and a processor, the memory for storing information including program instructions, and the processor for controlling the execution of the program instructions, characterized in that: When the program instructions are loaded and executed by the processor, they implement the steps of the dynamic allocation method for customer service in a customer service system as described in any one of claims 1 to 8.

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